An array of microphones can be used to locate and track a source of acoustic signals, e.g., a speaker or vehicle. Generally, this is called source localization.
One common method takes advantage of the time difference of arrival (TDOA) of the acoustic signal at the microphones. The TDOA can be estimated using a variety of techniques, “Special issue on time-delay estimation,” IEEE Transactions on Acoustics and Speech Signal Processing, vol. ASSP-29, June 1981, M. S. Brandstein, J. E. Adcock, and H. F. Silverman, “A practical time delay estimator for localizing speech sources with a microphone array,” Computer Speech and Language, vol. 9, pp. 153-169, April 1995, C. H. Knapp and G. C. Carter, “The generalized correlation method for estimation of time delay,” IEEE Transactions of Acoustics and Speech Signal Processing ASSP-24, 320327, 1976, and Benesty, J. “Adaptive eigenvalue decomposition algorithm for passive acoustic source localization,” Journal of the Acoustical Society of America, vol. 107, pp. 384-391, January 2000.
In conjunction with the positions of the microphones, the TDOA can be used to estimate the location of the source, R. Schmidt, “A new approach to geometry of range difference location,” IEEE Transactions of Aerospace and Electronic Systems, vol. AES-8, pp. 821-835, November 1972, J. Smith and J. Abel, “Closed-form least-squares source location estimation from range-difference measurements,” IEEE Transactions on Acoustics and Speech, Signal Processing, vol. ASSP-35, pp. 1661-1669, December 1987, and J. Smith and J. Abel, “The spherical interpolation method for closed-form passive source localization using range difference measurements,” Proceedings of the International Conference on Acoustics, Speech and Signal Processing (ICASSP), 1987.
Another method measures a likelihood that the signal originated from a set of locations instead of inferring the location from the input signal. That method can use a wide variety of computational techniques, including beam-forming and/or probabilistic formulations, S. T. Birtchfield and D. K. Gillmor, “Fast Bayesian acoustic localization,” Proceedings of the International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2002. Although that method is less efficient than the TDOA method, the method has better performance, and can operate reliably in environments with multiple sources.
Regardless of the localization technique used, it is imperative that the acoustics do not exhibit confusing reflections, the positions of the microphones are known, and the microphones have similar responses. Non-compliance with any of the above conditions can result in detrimental accuracy in localization estimates.
Therefore, it is desired to perform source localization in the case where the positioning and response of the microphones is unknown, where the acoustic environment is unknown, where there are strong reflections, and where there is constant background noise.